Python Developer

3 days ago

New Delhi, India Arcitech Full time

Python Developer Location: Turbhe, Navi Mumbai CTC: 5-12 LPA Years of Experience: 2-5 yearsIMMEDIATE JOINERS REQUIREDYour ResponsibilitiesAI/ML Engineering Develop, train, and optimize ML models using PyTorch, TensorFlow, and Keras. Build end-to-end LLM and RAG pipelines using LangChain and LangGraph. Work with LLM APIs (OpenAI, Anthropic Claude, Azure OpenAI) and implement prompt engineering strategies. Utilize Hugging Face Transformers for model fine-tuning and deployment. Integrate embedding models for semantic search and retrieval systems. Work with transformer-based architectures (BERT, GPT, LLaMA, Mistral) for production use cases. Implement LLM evaluation frameworks (RAGAS, LangSmith) and performance optimization. Backend & Systems Development Design and maintain Python microservices using Django and FastAPI with REST/GraphQL APIs. Implement real-time communication with Django Channels and FastAPI WebSockets. Design and optimize PostgreSQL databases with pgvector for embedding storage and similarity search. Integrate vector databases (Pinecone, Weaviate, FAISS, Milvus) for retrieval pipelines. Containerize AI services with Docker and deploy on Kubernetes (EKS/GKE/AKS). Configure AWS infrastructure (EC2, S3, RDS, SageMaker, Lambda, CloudWatch) for AI/ML workloads. Implement Redis caching and message brokers (RabbitMQ/Redis) with Celery for background tasks. Required Qualifications Bachelor's or Master's degree in Computer Science, AI/ML, or related field with 2–5 years of Python experience (Python 3.9+). Hands-on experience with LangChain and LangGraph for building LLM-powered workflows and RAG systems. Strong background in deep learning (PyTorch/TensorFlow), Hugging Face Transformers, and LLM APIs (OpenAI, Anthropic, Azure OpenAI). Proficiency with Django and FastAPI frameworks for building production APIs. Experience with PostgreSQL and pgvector for embedding storage and similarity search. Hands-on with MLOps (MLflow/W&B), Docker, Kubernetes, and AWS (EC2, S3, RDS, SageMaker). Skilled in Git workflows, automated testing (pytest), CI/CD, and AI security best practices. Excellent communication and analytical thinking. Nice to Have Experience with vector databases (Pinecone, Weaviate, FAISS, Milvus). Knowledge of advanced LLM fine-tuning (LoRA, QLoRA, PEFT) and RLHF. Experience with model serving frameworks and distributed training. Familiarity with workflow orchestration tools (Airflow, Prefect, Dagster). Knowledge of quantization and model compression techniques. Experience with infrastructure as code (Terraform, CloudFormation). Familiarity with data versioning tools (DVC) and AutoML. Experience with Streamlit or Gradio for ML demos. Background in statistics, optimization, or applied mathematics. Contributions to AI/ML or LangChain/LangGraph open-source projects.

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